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This paper explores how banks adjust their risk-based capital ratios and asset allocations following an exogenous shock to their asset quality caused by Hurricane Katrina in 2005. We find that independent banks based in the disaster areas increase their risk-based capital ratios after the hurricane, while those part of a bank holding company do not. The effect on independent banks mainly comes from the subgroup of high-capitalized banks. These banks increase their holdings in government securities and reduce loans to non-financial firms. Hence, banks that become more stable achieve this at the cost of reduced lending.

A number of recent studies regress a "narratively" identified measure of a macroeconomic shock directly on an outcome variable. In this note, we argue that this approach can be viewed as the reduced-form regression of an instrumental variable approach in which the narrative time series is used as an instrument for an endogenous series of interest. This motivates evaluating the validity of narrative measures through the lens of a randomized experiment. We apply our framework to four recently constructed narrative measures of tax shocks by Romer and Romer (2010), Cloyne (2013), and Mertens and Ravn (2012). All of them turn out to be weak instruments for observable measures of taxes. After correcting for weak instruments, we find that using any of the considered narrative tax measures as an instrument for cyclically adjusted tax revenues yields tax multiplier estimates that are indistinguishable from zero. We conclude that the literature currently understates the uncertainty associated with quantifying the tax multiplier.

This paper studies a dynamic stochastic general equilibrium model involving climate change. Our model allows for damages on economic growth resulting from global warming. In the calibration, we capture effects from climate change and feedback effects on the temperature dynamics. We solve for the optimal state-dependent abatement policy. In our simulations, the costs of this policy measured in terms of lost GDP growth are moderate. On the other hand, postponing abatement action could reduce the probability that the climate can be stabilized. For instance, waiting for 10 years reduces this probability from 60% to 30%. Waiting for another 10 years leads to a probability that is less than 10%. Finally, doing nothing opens the risk that temperatures might explode and economic growth decreases significantly.

The banking system is highly interconnected and these connections can be conveniently represented as an interbank network. This survey presents a systematic overview of the recent advances in the theoretical literature on interbank networks. We assess our current understanding of the structure of interbank networks, of how network characteristics affect contagion in the banking system and of how banks form connections when faced with the possibility of contagion and systemic risk. In particular, we highlight how the theoretical literature on interbank networks offers a coherent way of studying interconnections, contagion processes and systemic risk, while emphasizing at the same time the challenges that must be addressed before general results on the link between the structure of the interbank network and financial stability can be established. The survey concludes with a discussion of the policy relevance of interbank network models with a special focus on macroprudential policies and monetary policy.

It has been claimed for more than a century that atmospheric new particle formation is primarily influenced by the presence of sulfuric acid. However, the activation process of sulfuric acid related clusters into detectable particles is still an unresolved topic. In this study we focus on the PARADE campaign measurements conducted during August/September 2011 at Mt Kleiner Feldberg in central Germany. During this campaign a set of radicals, organic and inorganic compounds and oxidants and aerosol properties were measured or calculated. We compared a range of organic and inorganic nucleation theories, evaluating their ability to simulate measured particle formation rates at 3 nm in diameter (J3) for a variety of different conditions. Nucleation mechanisms involving only sulfuric acid tentatively captured the observed noon-time daily maximum in J3, but displayed an increasing difference to J3 measurements during the rest of the diurnal cycle. Including large organic radicals, i.e. organic peroxy radicals (RO2) deriving from monoterpenes and their oxidation products, in the nucleation mechanism improved the correlation between observed and simulated J3. This supports a recently proposed empirical relationship for new particle formation that has been used in global models. However, the best match between theory and measurements for the site of interest was found for an activation process based on large organic peroxy radicals and stabilised Criegee intermediates (sCI). This novel laboratory-derived algorithm simulated the daily pattern and intensity of J3 observed in the ambient data. In this algorithm organic derived radicals are involved in activation and growth and link the formation rate of smallest aerosol particles with OH during daytime and NO3 during night-time. Because the RO2 lifetime is controlled by HO2 and NO we conclude that peroxy radicals and NO seem to play an important role for ambient radical chemistry not only with respect to oxidation capacity but also for the activation process of new particle formation. This is supposed to have significant impact of atmospheric radical species on aerosol chemistry and should be taken into account when studying the impact of new particles in climate feedback cycles.

The use of decentralised, sustainable urban drainage systems (SUDS) for the treatment of stormwater runoff is becoming increasingly prevalent in Germany. Decentralised SUDS can offer a viable and attractive alternative to end of pipe treatment systems for stormwater runoff from urban areas. However, there is still some uncertainty regarding the long-term performance of SUDS, and the general legislative requirements for SUDS approval and testing. Whilst the allowable pollution levels in stormwater runoff that infiltrate into ground and/or water table are regulated across Germany by the Federal Soil Protection Law, there is presently no federal law addressing the discharge requirements for surface water runoff. The lack of clear guidance can make it difficult for planners and designers to implement these innovative and sustainable stormwater treatment systems. This study clarifies the current understanding of urban stormwater treatment requirements and new technical approval guidelines for decentralised SUDS devices in Germany. The study findings should assist researchers, designers and asset managers to better anticipate and understand the performance, effective life-spans, and the planning and maintenance requirements for decentralised SUDS systems. This should help promote even greater use of these systems in the future.

We present the application of Time-of-Flight Mass Spectrometry (TOF MS) for the analysis of halocarbons in the atmosphere, after cryogenic sample preconcentration and gas chromatographic separation. For the described field of application, the Quadrupole Mass Spectrometer (QP MS) is the state-of-the-art detector. This work aims at comparing two commercially available instruments, a QP MS and a TOF MS with respect to mass resolution, mass accuracy, sensitivity, measurement precision and detector linearity. Both mass spectrometers are operated on the same gas chromatographic system by splitting the column effluent to both detectors. The QP MS had to be operated in optimised Single Ion Monitoring (SIM) mode to achieve a sensitivity which could compete with the TOF MS. The TOF MS provided full mass range information in any acquired mass spectrum without losing sensitivity. Whilst the QP MS showed the performance already achieved in earlier tests, the sensitivity of the TOF MS was on average higher than that of the QP MS in the "operational" SIM mode by a factor of up to 3 reaching detection limits of less than 0.2 pg. Measurement precision determined for the whole analytical system was up to 0.2% depending on substance and sampled volume. The TOF MS instrument used for this study displayed significant non-linearities of up to 10% for two third of all analysed substances.

Immersion freezing is the most relevant heterogeneous ice nucleation mechanism through which ice crystals are formed in mixed-phase clouds. In recent years, an increasing number of laboratory experiments utilizing a variety of instruments have examined immersion freezing activity of atmospherically relevant ice-nucleating particles. However, an intercomparison of these laboratory results is a difficult task because investigators have used different ice nucleation (IN) measurement methods to produce these results. A remaining challenge is to explore the sensitivity and accuracy of these techniques and to understand how the IN results are potentially influenced or biased by experimental parameters associated with these techniques.
Within the framework of INUIT (Ice Nuclei Research Unit), we distributed an illite-rich sample (illite NX) as a representative surrogate for atmospheric mineral dust particles to investigators to perform immersion freezing experiments using different IN measurement methods and to obtain IN data as a function of particle concentration, temperature (T), cooling rate and nucleation time. A total of 17 measurement methods were involved in the data intercomparison. Experiments with seven instruments started with the test sample pre-suspended in water before cooling, while 10 other instruments employed water vapor condensation onto dry-dispersed particles followed by immersion freezing. The resulting comprehensive immersion freezing data set was evaluated using the ice nucleation active surface-site density, ns, to develop a representative ns(T) spectrum that spans a wide temperature range (−37 °C < T < −11 °C) and covers 9 orders of magnitude in ns.
In general, the 17 immersion freezing measurement techniques deviate, within a range of about 8 °C in terms of temperature, by 3 orders of magnitude with respect to ns. In addition, we show evidence that the immersion freezing efficiency expressed in ns of illite NX particles is relatively independent of droplet size, particle mass in suspension, particle size and cooling rate during freezing. A strong temperature dependence and weak time and size dependence of the immersion freezing efficiency of illite-rich clay mineral particles enabled the ns parameterization solely as a function of temperature. We also characterized the ns(T) spectra and identified a section with a steep slope between −20 and −27 °C, where a large fraction of active sites of our test dust may trigger immersion freezing. This slope was followed by a region with a gentler slope at temperatures below −27 °C. While the agreement between different instruments was reasonable below ~ −27 °C, there seemed to be a different trend in the temperature-dependent ice nucleation activity from the suspension and dry-dispersed particle measurements for this mineral dust, in particular at higher temperatures. For instance, the ice nucleation activity expressed in ns was smaller for the average of the wet suspended samples and higher for the average of the dry-dispersed aerosol samples between about −27 and −18 °C. Only instruments making measurements with wet suspended samples were able to measure ice nucleation above −18 °C. A possible explanation for the deviation between −27 and −18 °C is discussed. Multiple exponential distribution fits in both linear and log space for both specific surface area-based ns(T) and geometric surface area-based ns(T) are provided. These new fits, constrained by using identical reference samples, will help to compare IN measurement methods that are not included in the present study and IN data from future IN instruments.

Ongoing and predicted global change makes understanding and predicting species’ range shifts an urgent scientific priority. Here, we provide a synthetic perspective on the so far poorly understood effects of interspecific interactions on range expansion rates. We present theoretical foundations for how interspecific interactions may modulate range expansion rates, consider examples from empirical studies of biological invasions and natural range expansions as well as process-based simulations, and discuss how interspecific interactions can be more broadly represented in process-based, spatiotemporally explicit range forecasts. Theory tells us that interspecific interactions affect expansion rates via alteration of local population growth rates and spatial displacement rates, but also via effects on other demographic parameters. The best empirical evidence for interspecific effects on expansion rates comes from studies of biological invasions. Notably, invasion studies indicate that competitive dominance and release from specialized enemies can enhance expansion rates. Studies of natural range expansions especially point to the potential for competition from resident species to reduce expansion rates. Overall, it is clear that interspecific interactions may have important consequences for range dynamics, but also that their effects have received too little attention to robustly generalize on their importance. We then discuss how interspecific interactions effects can be more widely incorporated in dynamic modeling of range expansions. Importantly, models must describe spatiotemporal variation in both local population dynamics and dispersal. Finally, we derive the following guidelines for when it is particularly important to explicitly represent interspecific interactions in dynamic range expansion forecasts: if most interacting species show correlated spatial or temporal trends in their effects on the target species, if the number of interacting species is low, and if the abundance of one or more strongly interacting species is not closely linked to the abundance of the target species.